Efficiency of cluster schemes implementation for discrete dynamic programming for systems of support of dispatching technological processes in transport systems

Within the framework of a computationally complex canonical scheduling problem, formulated by an optimization model for one-processor servicing of a finite deterministic flow of objects, a scheme of computational process of an algorithm of discrete dynamic programming in cluster implementation is considered. Variants of balancing of computational subtasks over network cluster array are investigated, purposed to reduce the volume and intensity of intranetwork interaction. It has been established that for practical improvement of efficiency of cluster algorithm, it is required not to increase the uniformity of distribution of subtasks among the cluster nodes, but to minimize the network traffic between the cluster nodes. Balancing options are proposed that allow to significantly increase localization of data in network computing. Experimental results are analytically confirmed, showing the scaling limits of implementation of discrete dynamic programming algorithms on a cluster architecture. The method for choosing the number of computational nodes and dimension of the problem being solved, which provide a threefold reduction in overhead costs for network exchange, is shown. The results obtained make it possible to objectively substantiate the choice of methodological and algorithmic approaches when choosing computer tools developing architectural and technological solutions for dispatching systems support in inland water transport.

Encounter networks from collective mitochondrial dynamics support the emergence of effective mtDNA genomes in plant cells

Mitochondria in plant cells form strikingly dynamic populations of largely individual organelles. Each mitochondrion contains on average less than a full copy of the mitochondrial DNA (mtDNA) genome. Here, we asked whether mitochondrial dynamics may allow individual mitochondria to 'collect' a full copy of the mtDNA genome over time, by facilitating exchange between individuals. Akin to trade on a social network, exchange of mtDNA fragments across organelles may lead to the emergence of full 'effective' genomes in individuals over time. We characterise the collective dynamics of mitochondria in Arabidopsis thaliana hypocotyl cells using a recent approach combining single-cell timelapse microscopy, video analysis, and network science. We then use a quantitative model to predict the capacity for the sharing and accumulation of genetic information through the networks of encounters between mitochondria. We find that biological encounter networks are strikingly well predisposed to support the collection of full genomes over time, outperforming a range of other networks generated from theory and simulation. Using results from the coupon collector's problem, we show that the upper tail of the degree distribution is a key determinant of an encounter network's performance at this task and discuss how features of mitochondrial dynamics observed in biology facilitate the emergence of full effective genomes.

Finite-Level Quantized Consensus of Multi-agent Networked Systems

This paper is concerned with the analysis of consensus multi-agent networked system. Adopted in the analysis is the finite-level logarithmic quantizer, for the transmission of the networked-agents state. Two protocols are utilised in the analysed multi-agent networked system: the consensus protocol, which is determined from the outputs and states of a set of encoder-decoder pair that is employed in the system, and convergence rate protocol that is precisely characterized via the use of a dynamic scaling factor. With information exchange among neighbouring agents, the asymptotic consensus can be reached. The proof of protocols is based on proper selection of parameters of the logarithmic quantizer chosen for the connected network. As a demonstration of the validity of the protocols, a four-agent networked system is used. It is shown that an undirected network exchange of information via a communication channel that is equipped with a set of encoder and decoder can lead to attainment of estimates of neighbour state protocol for the networked system. Furthermore, desired asymptotic convergence can be reached through appropriate choice of parameters of the logarithmic quantizer.

Dynamic covalent chemistry for architecture changing interpenetrated and single networks

Dynamic single and interpenetrated materials were developed, with post polymerization network exchange enhancing the material properties.

A leader–network exchange theory

PurposeWe propose an integrative model of how leaders (individual level) effectively relate to their social networks as a whole (network level). Additionally, we focus both on the leader constructs and the followers shared constructs about those networks.Design/methodology/approachOur conceptual paper uses the integration of literature from two main bodies of knowledge: individual and shared cognitions, fundamentally from psychology, and a structural perspective, mainly from sociology, organisational studies and social network analysis. We take a psycho-structural approach which allows the emergence of new perspectives on the study of leadership and more specifically on the study of relational leadership.FindingsWe propose a leader-network exchange (LNX) theory focussed on the behaviours and cognitions of leaders and followers as well as the relations between them.Research limitations/implicationsOur model represents a new perspective on leader–followers relationship by stressing the importance of both followers and leaders' cognitions. We highlight the importance of the relationships between followers on the creation of shared meaning about the leader.Practical implicationsOur model helps leaders and managers make sense of the cognitions and behaviours of their teams. By considering the teams characteristics, i.e. cognitions and network structure, it allows leaders to adopt the most appropriate behaviours for effective leadership. Leadership and management development programmes designed around our model will enhance the use of networking skills.Originality/valueContrary to the traditional view of LMX, our approach considers the social context of leaders and followers. It also adds a new layer of knowledge going beyond what members think of their leaders by considering the social networks of leaders and followers.

Examining Patterns of Information Exchange and Social Support in a Web-Based Health Community: Exponential Random Graph Models

Background Although an increasing number of studies have attempted to understand how people interact with others in web-based health communities, studies focusing on understanding individuals’ patterns of information exchange and social support in web-based health communities are still limited. In this paper, we discuss how patients’ social interactions develop into social networks based on a network exchange framework and empirically validate the framework in web-based health care community contexts. Objective This study aims to explore various patterns of information exchange and social support in web-based health care communities and identify factors that affect such patterns. Methods Using social network analysis and text mining techniques, we empirically validated a network exchange framework on a 10-year data set collected from a popular web-based health community. A reply network was extracted from the data set, and exponential random graph models were used to discover patterns of information exchange and social support from the network. Results Results showed that reciprocated information exchange was common in web-based health communities. The homophily effect existed in general conversations but was weakened when exchanging knowledge. New members in web-based health communities tended to receive more support. Furthermore, polarized sentiment increases the chances of receiving replies, and optimistic users play an important role in providing social support to the entire community. Conclusions This study complements the literature on network exchange theories and contributes to a better understanding of social exchange patterns in the web-based health care context. Practically, this study can help web-based patients obtain information and social support more effectively.

Using plant leaders' perspectives to overcome barriers to inter-plant exchange

PurposeThis paper sets out to identify barriers to intra-network exchange within international manufacturing networks (IMNs) from the micro-level perspective of key actors at the plant level, namely, plant leaders.Design/methodology/approachData were collected through interviews with 12 plant leaders from nine different firms operating in at least three geographically dispersed manufacturing facilities.FindingsSix partially interrelated barriers to intra-network exchange were identified. First, there are a lack of resources, network strategies, plant overlap and individual-level ties between plant leaders. Furthermore, this study shows that the pronounced local focus of plant leaders, fierce inter-plant competition and falsely designed incentives constitute barriers to inter-plant exchange. The results underline the need for network management to consider the individual-level perspective when designing rules and policies for IMNs.Research limitations/implicationsThe generalisability of the results is limited by the sample, which consists of plant leaders from firms headquartered in German-speaking areas.Practical implicationsThe findings indicate that network managers should consider the interests and concerns of plant leaders when trying to facilitate network thinking. In addition to delayering the overall IMN into distinct subnetworks of peer plants, network managers should set clear and openly communicated objectives in a mission for each subnetwork that also points to inter-plant exchange and provides the resources for such activities. Practitioners should also apply shared objectives for plant leaders and promote individual-level ties between them to benefit from intra-network exchange.Originality/valueBy analysing the perceptions of plant leaders, this study sheds light on the individual level of global operations, which has been neglected in research on IMNs to date.

The effect of combining nanosilver and new injection form of rexod on the periodontal tissues state on experimental periodontitis in rats

A representative and randomized study of the effect of a combination of nanosilver and a new injection form of Rexod® on the periodontal tissues state of animals (rats) in an experimental model of inflammatory pathology of periodontal tissues (experimental periodontitis) was carried out. It was shown that the improvement of the dental status of periodontal tissues against the background of the course application of a combination of nanosilver (topically) and a new injection form of Rexod® was accompanied by a decrease in the amount of gingival fluid of the sulcular gingival sulcus, an improvement in the clinical condition of the marginal periodontal mucosa (hyperemia was leveled, swelling decreased, the bleeding indexPBI Muhllemann-Cowell decreased, test Schiller-Pisarev results normalised). The decrease in the number of gum fluids is due to the decrease in antibacterial activity of pathogenic microflora and their products of their life-based hemodynamics of the peripheral microvascular network (exchange capabulars) of the periodontal, a decrease in perfusion pressure in them, reduced (narrowing) of their lumen, reduce their permeability and restoration of oxidation-reduction processes.

Examining Patterns of Information Exchange and Social Support in a Web-Based Health Community: Exponential Random Graph Models (Preprint)

BACKGROUND Although an increasing number of studies have attempted to understand how people interact with others in web-based health communities, studies focusing on understanding individuals’ patterns of information exchange and social support in web-based health communities are still limited. In this paper, we discuss how patients’ social interactions develop into social networks based on a network exchange framework and empirically validate the framework in web-based health care community contexts. OBJECTIVE This study aims to explore various patterns of information exchange and social support in web-based health care communities and identify factors that affect such patterns. METHODS Using social network analysis and text mining techniques, we empirically validated a network exchange framework on a 10-year data set collected from a popular web-based health community. A reply network was extracted from the data set, and exponential random graph models were used to discover patterns of information exchange and social support from the network. RESULTS Results showed that reciprocated information exchange was common in web-based health communities. The homophily effect existed in general conversations but was weakened when exchanging knowledge. New members in web-based health communities tended to receive more support. Furthermore, polarized sentiment increases the chances of receiving replies, and optimistic users play an important role in providing social support to the entire community. CONCLUSIONS This study complements the literature on network exchange theories and contributes to a better understanding of social exchange patterns in the web-based health care context. Practically, this study can help web-based patients obtain information and social support more effectively.